The following invention relates to a system and method for providing a client with a price for a security and, in particular, for a system and method for dynamically adjusting price quotes generated by an automated trading system.
Financial institutions often use automated trading systems to support their clients' trading requests. Generally, these automated trading systems provide the client with price quotes upon which the client may base a trading decision. Such trading systems may provide price quotes for any type of security such as FX securities, equities, commodities and debt instruments. (See, for example, Kalmus et al., “Automated Securities Trading System, U.S. Pat. No. 4,674,044).
Referring now to FIG. 1, there is shown a block diagram of an exemplary prior art trading system 10. Trading system 10, operated by a financial institution, is accessed by a client access device, operated by a client, for receiving price quotes in securities and issuing trade requests in such securities. Trading system 10 includes a pricing engine 14 that calculates a price quote in response to a client price request using known pricing techniques based on real-time market information (for e.g., interest rate information). A responsive price quote may also be provided manually such as directly by a salesperson and/or trader. Upon receiving a price quote, the client may indicate to trading system 10 a desire to trade in the particular security based on the price quote. Trading system 10 also includes a settlement system 15 for implementing the steps required to credit the requested trade to the client's account and a hedging module 16 that interfaces with external markets for eliminating any risk to the financial institution as a result of accepting the trade.
Financial institutions typically take into consideration the type and size of the client when providing the client with a price quote. For example, the financial institution may quote better prices to those clients that provide the financial institution with a larger amount of trading business. To provide this price differentiation in the context of an automated trading system, some prior art pricing engines provide a client with price quotes from one of a discrete number of pricing levels. The pricing level that is given to a particular client is based on the volume of trading the client has done with the financial institution. So, for example, if a client has provided the financial institution with a significant amount of trading business, that client may placed in a more favorable (to the client) pricing level. Thus, when the client requests a price quote from the trading system, the pricing engine will provide the client with price quotes according to the designated pricing level.
A drawback of the pricing engines of prior art trading systems is that the prices that are provided to clients are either uniform for all clients or are based on a limited number of discrete pricing levels. First, a discrete number of pricing levels is often insufficient and cumbersome for providing tailored price quotes to a large client base. Also, basing price level selection on the particular client's prior trading volume does not always reflect the current value of the client to the financial institution. For instance, other characteristics of the client, such as the client's trading patterns and profits generated, may often be useful as a basis for adjusting pricing. Furthermore, the prior art pricing engines do not dynamically adjust pricing in order to achieve a specific result such as, for example, maximizing profits per customer or increasing overall trading volume. Accordingly, it is desirable to provide a system and method for dynamically adjusting price quotes generated by an automated trading system.